Paper Title
FB K-Entailing: An Incipient Algorithm With Feedback Sessions For User Search Goals
Abstract
The information on the web is growing dramatically. Without a recommendation system, the users
may spend lots of time on the web in finding the information they are interested in. The rapid growth of internet
has pushed the research and development of web usage mining even more into focus. Analyzing user’s web log
data and extracting their interests are important and challenging research topics of web usage mining. User’s
web watching behaviors can be regarded as a graph since visited Web sites and entered search keywords are
connected with each other in a time sequence. In this paper we present a novel approach of extracting user’s
interests from Web Log using k-means,fuzzy and BiSecting Algorithms. We produce the performance of user
search goals based on “Classified Average Precision(CAP)”.